Drop paths (Stochastic Depth) per sample (when applied in main path of residual blocks).

Inject some information about the relative or absolute position of the tokens in the sequence. The positional encodings have the same dimension as

Unified OpenOCR interface that dispatches to different task implementations. Supported tasks: - 'det': Text detection only - 'rec':

Subclass torch's LayerNorm to handle fp16.

LayerNorm that supports two data formats: channels_last (default) or channels_first. The ordering of the dimensions in the inputs. channels_last

Convert structured recognition results to Markdown format

ONNX-based inference for UniRec model (standalone version).

完整的文档OCR ONNX Pipeline

PPHGNet Args: stem_channels: list. Stem channel list of PPHGNet. stage_config: dict. The configuration of each stage of PPHGN

r"""Focal Modulation Network Block. Args: dim (int): Number of input channels. input_resolution (tuple[int]): Input resulotion.

SE Module as defined in original SE-Nets with a few additions Additions include: * divisor can be specified to keep channels % div == 0 (d

SE Module as defined in original SE-Nets with a few additions Additions include: * divisor can be specified to keep channels % div == 0 (d

Track a series of values and provide access to smoothed values over a window or the global series average.

TableCell represents a single cell in a table. Attributes: row_span (int): Number of rows spanned. col_span (int): Number of

This code is refered from: https://github.com/MhLiao/DB/blob/master/decoders/feature_attention.py